Package: monomvn
Type: Package
Title: Estimation for MVN and Student-t Data with Monotone Missingness
Version: 1.9-20
Date: 2024-01-11
Author: Robert B. Gramacy <rbg@vt.edu>, with Fortran contributions from Cleve Moler (dpotri/LINPACK) as updated by Berwin A. Turlach (qpgen2/quadprog)
Maintainer: Robert B. Gramacy <rbg@vt.edu>
Description: Estimation of multivariate normal (MVN) and student-t data of 
 arbitrary dimension where the pattern of missing data is monotone.
 See Pantaleo and Gramacy (2010) <arXiv:0907.2135>.
 Through the use of parsimonious/shrinkage regressions 
 (plsr, pcr, lasso, ridge,  etc.), where standard regressions fail, 
 the package can handle a nearly arbitrary amount of missing data. 
 The current version supports maximum likelihood inference and 
 a full Bayesian approach employing scale-mixtures for Gibbs sampling.
 Monotone data augmentation extends this Bayesian approach to arbitrary 
 missingness patterns.  A fully functional standalone interface to the 
 Bayesian lasso (from Park & Casella), Normal-Gamma (from Griffin & Brown),
 Horseshoe (from Carvalho, Polson, & Scott), and ridge regression 
 with model selection via Reversible Jump, and student-t errors 
 (from Geweke) is also provided.
Depends: R (>= 2.14.0), pls, lars, MASS
Imports: quadprog, mvtnorm
License: LGPL
URL: https://bobby.gramacy.com/r_packages/monomvn/
NeedsCompilation: yes
Packaged: 2024-01-11 13:22:50 UTC; bobby
Repository: CRAN
Date/Publication: 2024-01-11 14:20:02 UTC
Built: R 4.4.0; x86_64-apple-darwin20.6.0; 2024-05-08 23:04:55 UTC; unix
